Quantifying Rare Events, ICAAP and SMA

This course presents in simple terms the sound techniques to measure rare events, quantify operational risk scenarios and address the challenge of ICAAP and capital assessment for the financials services.

About the course

This online course presents in simple terms the sound techniques to measure rare events, quantify operational risk scenarios and address the challenge of ICAAP and capital assessment for the financials services.

Targeted to an audience with some quantitative background, this course is also suitable for managers with little or no technical knowledge, but keen to feel able to review the ICAAP process and the capital numbers prepared by specialist.

The course is an executive version of the academic lecture “Operational risk measurement for the financial services” taught by Dr. Chapelle at University College London. The course will present some of the latest research in the field of reputation impact measurement from operational risk events, using machine learning.

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What will you learn?
  • The role of scenarios in an ERM framework and how to identify and select scenarios
  • The influence of Covid-19 on scenario identification and assessment  
  • Best practice and regulatory guidance for ICAAP for small firms
  • The role of regulatory capital and the changes with SMA
  • The role of pillar 2 under the new SMA regime
  • Recent developments in op risk quantification and machine learning
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Who Should Attend?

Relevant departments may include but are not limited to:

  • Heads of operational risk
  • Enterprise risk managers
  • Operational risk managers
  • Operations managers
  • Internal auditors
  • Compliance officers
  • Consultants
  • Regulators
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Sessions Include
  • The role of scenarios in a post-Covid world
  • Regulatory context: SMA, ICAAP, and operational scenarios  
  • Scenario analysis step by step
  • Scenario assessment 1: methods for quantifying rare events  
  • Scenario assessment 2: operational risk measurement in practice
  • Measuring reputation impact: latest research using machine learning
  • Model risk and model validation  
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Pricing Options

We offer flexible pricing options for this course:

  • Early bird rates - save up to $500

  • Group booking rate - save over $1500

  • Subscribe to receive Risk Training updates and avoid missing out on additional savings 

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Ariane Chapelle

Adjunct professor

University College London

Dr, Ariane Chapelle, is Honorary Reader at University College London and is an internationally recognised trainer and consultant in Risk. She teaches at UCL 'Operational Risk Measurement for Financial Institutions’ and is a Fellow of the Institute of Operational Risk..

In 2019, the firm received the Risk.net Award for ‘Outstanding Achievement in the Year in Operational Risk’. She published at Wiley Finance Series the textbook Operational Risk Management: Best Practices in the Financial Services Industry, in December 2018 that rapidly became the No.1 best seller in its field and is now translated in French by Pearson France. In 2020, the book got elected “Book of the Year” by risk.net.

Dr. Chapelle founded and runs her adivsory and training practice in risk management, serving all sizes of financial organisations and international institutions, including central banks and UN agencies. She is a former holder of the Chair of International Finance at the University of Brussels with backgrounds in internal audit, credit risk and investment risk. She has been active in operational risk management since 2000 and was formerly head of operational risk management at ING Group and Lloyds Banking Group.

Natalie Gapp

research consultant

Chapelle Consulting

Natalie Gapp is a research consultant at Chapelle Consulting and co-founder of Chapelle Analytics, one of its subsidiaries. Natalie holds a Master degree in Computational Finance from University College London (UCL) where her study centered around data analysis, statistics, and operational risk.

She is currently working toward a PhD in machine learning applied to operational risk and reputation impact through UCL. Her current research focuses on building machine learning models for operational risk prediction and the measurement of reputation damage to firm following adverse news. Natalie previously built machine learning models for financial news analysis during work on her MSc dissertation. 

Alongside her research activity, she is developing ML online training courses for general managers and advanced courses on ML techniques and coding.

In her prior work she taught high school special education maths courses in New York City. As a teacher, she sought to create engaging curriculum that used real-world applications to make content relevant beyond the classroom.

Live Virtual training courses

 

Our live virtual training courses have been designed to engage and inspire you. Much more than a webinar, our approach includes:

  • Technical content compressed into 60-minute interactive sessions and spread out over two, three or four days

  • Facilitated collaboration including Q&A, interactive polling and group workshops

  • Live interaction with subject matter experts – get your questions answered in real time

  • Receive comprehensive course materials and supporting content from Risk.net to reinforce your learning

  • Stay connected with other learners and extend your network by joining our dedicated LinkedIn group for course participants